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| Extracting Weapon Attributes Based on Word Completion |
Ding Shengchun( ),You Weijing,Wang Xiaoying |
| School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China |
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Abstract [Objective] This paper tries to address the issue facing dependency syntactic relation, which could only extract single noun attributes for military equipment. [Methods] First, we analyzed features of the text describing the technology and performance of weapons and equipment. Then, we wrote regular expressions to obtain the attribute values. Third, we extracted the attribute words based on dependency parsing. Finally, we completed the attribute word lists with the part of speech. [Results] We examined our new model with military news data sets and found the accuracy and recall rates for extracting open-source attribute words reached 91.53% and 72.78%. The accuracy of attribute word completion was up to 96.95%, and the accuracy for each category of attribute words was higher than 90%. [Limitations] This paper did not try to extract weapon attributes like the belonging country and the state of service. [Conclusions] The proposed method could effectively extract explicit attribute words.
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Received: 31 August 2021
Published: 14 April 2022
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| Fund:Social Science Fund of Jiangsu Province(20TQB004) |
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Corresponding Authors:
Ding Shengchun,ORCID：0000-0002-4269-021X
E-mail: todingding@163.com
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